Abstract
Compressive sensing is a technique that can sample compressible signals below the traditional rate. One of fundamental problems in compressive sensing is the sparse signal recovery. Recently, alternating projection method was proposed for this kind of recovery. Two sufficient conditions for the recovery guarantee of the method were also given. In this paper, we establish another sufficient condition for the recovery guarantee of alternating projection method in terms of the restricted isometry constants and singular values of the measurement matrix, it is a useful improvement on one of the existing two conditions. The famous Weyl inequality, Cauchy interlace theorem and partition skills of involved matrices are utilized. The requirement for the measurement matrix is lowered. Thus, this improvement allows more measurement matrices to be used for alternating projection method. This can enhance the applicability of the method.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
